Title |
Single cell transcriptomic analysis of prostate cancer cells
|
---|---|
Published in |
BMC Molecular and Cell Biology, February 2013
|
DOI | 10.1186/1471-2199-14-6 |
Pubmed ID | |
Authors |
Christopher J Welty, Ilsa Coleman, Roger Coleman, Bryce Lakely, Jing Xia, Shu Chen, Roman Gulati, Sandy R Larson, Paul H Lange, Bruce Montgomery, Peter S Nelson, Robert L Vessella, Colm Morrissey |
Abstract |
The ability to interrogate circulating tumor cells (CTC) and disseminated tumor cells (DTC) is restricted by the small number detected and isolated (typically <10). To determine if a commercially available technology could provide a transcriptomic profile of a single prostate cancer (PCa) cell, we clonally selected and cultured a single passage of cell cycle synchronized C4-2B PCa cells. Ten sets of single, 5-, or 10-cells were isolated using a micromanipulator under direct visualization with an inverted microscope. Additionally, two groups of 10 individual DTC, each isolated from bone marrow of 2 patients with metastatic PCa were obtained. RNA was amplified using the WT-Ovation™ One-Direct Amplification System. The amplified material was hybridized on a 44K Whole Human Gene Expression Microarray. A high stringency threshold, a mean Alexa Fluor® 3 signal intensity above 300, was used for gene detection. Relative expression levels were validated for select genes using real-time PCR (RT-qPCR). |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 3 | 5% |
United Kingdom | 1 | 2% |
India | 1 | 2% |
Unknown | 59 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 16 | 25% |
Researcher | 16 | 25% |
Student > Master | 7 | 11% |
Student > Doctoral Student | 6 | 9% |
Student > Bachelor | 4 | 6% |
Other | 8 | 13% |
Unknown | 7 | 11% |
Readers by discipline | Count | As % |
---|---|---|
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Biochemistry, Genetics and Molecular Biology | 11 | 17% |
Medicine and Dentistry | 9 | 14% |
Engineering | 4 | 6% |
Immunology and Microbiology | 1 | 2% |
Other | 2 | 3% |
Unknown | 10 | 16% |